@article{Gao2018,
title = {Genome-Wide Association Analyses Identify New Loci Influencing Intraocular Pressure},
author = {XR Gao and H Huang and DR Nannini and F Fan and H Kim},
url = {https://www.ncbi.nlm.nih.gov/pubmed/29617998},
year = {2018},
date = {2018-03-28},
journal = {Human molecular genetics},
abstract = {Elevated intraocular pressure (IOP) is a significant risk factor for glaucoma, the leading cause of irreversible blindness worldwide. While previous studies have identified numerous genetic variants associated with IOP, these loci only explain a fraction of IOP heritability. Recent establishments of biobank repositories have resulted in large amounts of data, enabling the identification of the remaining heritability for complex traits. Here, we describe the largest genome-wide association study of IOP to date using participants of European ancestry from the UK Biobank. We identified 671 directly genotyped variants that are significantly associated with IOP (P < 5 × 10-8). In addition to 103 novel loci, the top ranked novel IOP genes are LMX1B, NR1H3, MADD, and SEPT9. We replicated these findings in an external population and examined the pleiotropic nature of these loci. These discoveries not only further our understanding of the genetic architecture of IOP, but also shed new light on the biological processes underlying glaucoma.},
keywords = {23424, genetics, Intraocular pressure},
pubstate = {published},
tppubtype = {article}
}

Elevated intraocular pressure (IOP) is a significant risk factor for glaucoma, the leading cause of irreversible blindness worldwide. While previous studies have identified numerous genetic variants associated with IOP, these loci only explain a fraction of IOP heritability. Recent establishments of biobank repositories have resulted in large amounts of data, enabling the identification of the remaining heritability for complex traits. Here, we describe the largest genome-wide association study of IOP to date using participants of European ancestry from the UK Biobank. We identified 671 directly genotyped variants that are significantly associated with IOP (P < 5 × 10-8). In addition to 103 novel loci, the top ranked novel IOP genes are LMX1B, NR1H3, MADD, and SEPT9. We replicated these findings in an external population and examined the pleiotropic nature of these loci. These discoveries not only further our understanding of the genetic architecture of IOP, but also shed new light on the biological processes underlying glaucoma.

PURPOSE: To describe the associations of physical and demographic factors with Goldmann-correlated intraocular pressure (IOPg) and corneal-compensated intraocular pressure (IOPcc) in a British cohort. DESIGN: Cross-sectional study within the UK Biobank, a large-scale multisite cohort study in the United Kingdom. PARTICIPANTS: We included 110 573 participants from the UK Biobank with intraocular pressure (IOP) measurements available. Their mean age was 57 years (range, 40-69 years); 54% were women, and 90% were white. METHODS: Participants had 1 IOP measurement made on each eye using the Ocular Response Analyzer noncontact tonometer. Linear regression models were used to assess the associations of IOP with physical and demographic factors. MAIN OUTCOME MEASURES: The IOPg and IOPcc. RESULTS: The mean IOPg was 15.72 mmHg (95% confidence interval [CI], 15.70-15.74 mmHg), and the mean IOPcc was 15.95 mmHg (15.92-15.97 mmHg). After adjusting for covariates, IOPg and IOPcc were both significantly associated with older age, male sex, higher systolic blood pressure (SBP), faster heart rate, greater myopia, self-reported glaucoma, and colder season (all P < 0.001). The strongest determinants of both IOPg and IOPcc were SBP (partial R(2): IOPg 2.30%, IOPcc 2.26%), followed by refractive error (IOPg 0.60%, IOPcc 1.04%). The following variables had different directions of association with IOPg and IOPcc: height (-0.77 mmHg/m IOPg; 1.03 mmHg/m IOPcc), smoking (0.19 mmHg IOPg, -0.35 mmHg IOPcc), self-reported diabetes (0.41 mmHg IOPg, -0.05 mmHg IOPcc), and black ethnicity (-0.80 mmHg IOPg, 0.77 mmHg IOPcc). This suggests that height, smoking, diabetes, and ethnicity are related to corneal biomechanical properties. The increase in both IOPg and IOPcc with age was greatest among those of mixed ethnicities, followed by blacks and whites. The same set of covariates explained 7.4% of the variability of IOPcc but only 5.3% of the variability of IOPg. CONCLUSIONS: This analysis of associations with IOP in a large cohort demonstrated that some variables clearly have different associations with IOPg and IOPcc, and that these 2 measurements may reflect different biological characteristics.